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Mystical Tutor: A Magic: The Gathering Design Assistant via Denoising Sequence-to-Sequence Learning 神秘导师:魔法:通过去噪序列到序列学习的收集设计助手
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v12i1.12851
A. Summerville, Michael Mateas
{"title":"Mystical Tutor: A Magic: The Gathering Design Assistant via Denoising Sequence-to-Sequence Learning","authors":"A. Summerville, Michael Mateas","doi":"10.1609/aiide.v12i1.12851","DOIUrl":"https://doi.org/10.1609/aiide.v12i1.12851","url":null,"abstract":"\u0000 \u0000 Procedural Content Generation (PCG) has seen heavy focus on the generation of levels for video games, aesthetic content, and on rule creation, but has seen little use in other domains. Recently, the ready availability of Long Short Term Memory Recurrent Neural Networks (LSTM RNNs) has seen a rise in text based procedural generation, including card designs for Collectible Card Games (CCGs) like Hearthstone or Magic: The Gathering. In this work we present a mixed-initiative design tool, Mystical Tutor, that allows a user to type in a partial specification for a card and receive a full card design. This is achieved by using sequence-to-sequence learning as a denoising sequence autoencoder, allowing Mystical Tutor to learn how to translate from partial specifications to full.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"43 1","pages":"86-92"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74991462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
Improvised Theatre Alongside Artificial Intelligences 即兴戏剧与人工智能并存
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12926
K. Mathewson, Piotr Wojciech Mirowski
{"title":"Improvised Theatre Alongside Artificial Intelligences","authors":"K. Mathewson, Piotr Wojciech Mirowski","doi":"10.1609/aiide.v13i1.12926","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12926","url":null,"abstract":"\u0000 \u0000 This study presents the first report of Artificial Improvisation, or improvisational theatre performed live, on-stage, alongside an artificial intelligence-based improvisational performer. The Artificial Improvisor is a form of artificial conversational agent, or chatbot, focused on open domain dialogue and collaborative narrative generation. Using state-of-the-art machine learning techniques spanning from natural language processing and speech recognition to reinforcement and deep learning, these chatbots have become more lifelike and harder to discern from humans. Recent work in conversational agents has been focused on goal-directed dialogue focused on closed domains such as appointment setting, bank information requests, question-answering, and movie discussion. Natural human conversations are seldom limited in scope and jump from topic to topic, they are laced with metaphor and subtext and face-to-face communication is supplemented with non-verbal cues. Live improvised performance takes natural conversation one step further with multiple actors performing in front of an audience. In improvisation the topic of the conversation is often given by the audience several times during the performance. These suggestions inspire actors to perform novel, unique, and engaging scenes. During each scene, actors must make rapid fire decisions to collaboratively generate coherent narratives. We have embarked on a journey to perform live improvised comedy alongside artificial intelligence systems. We introduce Pyggy and A.L.Ex. (Artificial Language Experiment), the first two Artificial Improvisors, each with a unique composition and embodiment. This work highlights research and development, successes and failures along the way, celebrates collaborations enabling progress, and presents discussions for future work in the space of artificial improvisation.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"145 1","pages":"66-72"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87617112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 33
Merits of Hierarchical Story and Discourse Planning with Merged Languages 层次故事与融合语言语篇规划的优点
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12945
David R. Winer, R. Young
{"title":"Merits of Hierarchical Story and Discourse Planning with Merged Languages","authors":"David R. Winer, R. Young","doi":"10.1609/aiide.v13i1.12945","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12945","url":null,"abstract":"\u0000 \u0000 A hierarchical, bipartite model can characterize many complex narrative phenomena associated with coordinating plot and communication in storytelling (e.g., cinematography), but the predominant pipeline-based strategy for generating narratives has inadvertently limited the expressiveness of storytelling systems. We introduce computational steps for merging story and discourse languages in plan-based storytelling systems with hierarchical knowledge which avoids this problem and motivates more expressive narrative discourse reasoning.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"31 1","pages":"262-269"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88957870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Procedural Level Generation for Augmented Reality Games 增强现实游戏的程序关卡生成
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v12i1.12850
Sasha Azad, Carl Saldanha, Cheng-Hann Gan, Mark O. Riedl
{"title":"Procedural Level Generation for Augmented Reality Games","authors":"Sasha Azad, Carl Saldanha, Cheng-Hann Gan, Mark O. Riedl","doi":"10.1609/aiide.v12i1.12850","DOIUrl":"https://doi.org/10.1609/aiide.v12i1.12850","url":null,"abstract":"\u0000 \u0000 Mixed reality games are those in which virtual graphical assets are overlaid on the physical world. We explore the use of procedural content generation to enhance the gameplay experience in a prototype mixed reality game. Procedural content generation is used to design levels that make use of the affordances in the player’s physical environment. Levels are tailored to gameplay difficulty and to affect how the player moves their physical body in the real world.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"1 1","pages":"247-250"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75514269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Game Level Generation from Gameplay Videos 从游戏视频中生成游戏关卡
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v12i1.12861
Matthew J. Guzdial, Mark O. Riedl
{"title":"Game Level Generation from Gameplay Videos","authors":"Matthew J. Guzdial, Mark O. Riedl","doi":"10.1609/aiide.v12i1.12861","DOIUrl":"https://doi.org/10.1609/aiide.v12i1.12861","url":null,"abstract":"\u0000 \u0000 We present an unsupervised process to generate full video game levels from a model trained on gameplay video. The model represents probabilistic relationships between shapes properties, and relates the relationships to stylistic variance within a domain. We utilize the classic platformer game Super Mario Bros. to evaluate this process due to its highly-regarded level design. We evaluate the output in comparison to other data-driven level generation techniques via a user study and demonstrate its ability to produce novel output more stylistically similar to exemplar input.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"24 1","pages":"44-50"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74805814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 67
A Social Robot as a Card Game Player 作为纸牌游戏玩家的社交机器人
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12936
Filipa Correia, Patrícia Alves-Oliveira, T. Ribeiro, Francisco S. Melo, A. Paiva
{"title":"A Social Robot as a Card Game Player","authors":"Filipa Correia, Patrícia Alves-Oliveira, T. Ribeiro, Francisco S. Melo, A. Paiva","doi":"10.1609/aiide.v13i1.12936","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12936","url":null,"abstract":"\u0000 \u0000 This paper describes a social robotic game player that is able to successfully play a team card game called Sueca. The question we will address in this paper is: how can we build a social robot player that is able to balance its ability to play the card game with natural and social behaviours towards its partner and its opponents. The first challenge we faced concerned the development of a competent artificial player for a hidden information game, whose time constraint is the average human decision time. To accomplish this requirement, the Perfect Information Monte Carlo (PIMC) algorithm was used. Further, we have performed an analysis of this algorithm's possible parametrizations for games trees that cannot be fully explored in a reasonable amount of time with a MinMax search. Additionally, given the nature of the Sueca game, such robotic player must master the social interactions both as a partner and as an opponent. To do that, an emotional agent framework (FAtiMA) was used to build the emotional and social behaviours of the robot. At each moment, the robot not only plays competitively but also appraises the situation and responds emotionally in a natural manner. To test the approach, we conducted a user study and compared the levels of trust participants attributed to the robots and to human partners. Results have shown that the robot team exhibited a winning rate of 60%. Concerning the social aspects, the results also showed that human players increased their trust in the robot as their game partners (similar to the way to the trust levels change towards human partners).\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"44 1","pages":"23-29"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74176404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 29
Generative Design for Textiles: Opportunities and Challenges for Entertainment AI 纺织品的生成设计:娱乐人工智能的机遇与挑战
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12925
Gillian Smith
{"title":"Generative Design for Textiles: Opportunities and Challenges for Entertainment AI","authors":"Gillian Smith","doi":"10.1609/aiide.v13i1.12925","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12925","url":null,"abstract":"\u0000 \u0000 This paper reports on two generative systems that work in the domain of textiles: the Hoopla system that generates patterns for embroidery samplers, and the Foundry system that creates foundation paper piecing patterns for quilts. Generated patterns are enacted and interpreted by the human who stitches the final product, following a long and laborious, yet entertaining and leisurely, process of stitching and sewing. The blending of digital and physical spaces, the tension between machine and human authorship, and the juxtaposition of stereotypically masculine computing with highly feminine textile crafts, leads to the opportunity for new kinds of tools, experiences, and artworks. This paper argues for the values of textiles as a domain for generative methods research, and discusses generalizable research problems that are highlighted through operating in this new domain.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"3 1","pages":"115-121"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85375966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Fast Random Genetic Search for Large-Scale RTS Combat Scenarios 大规模RTS战斗场景的快速随机遗传搜索
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12955
C. Clark, Anthony Fleshner
{"title":"Fast Random Genetic Search for Large-Scale RTS Combat Scenarios","authors":"C. Clark, Anthony Fleshner","doi":"10.1609/aiide.v13i1.12955","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12955","url":null,"abstract":"\u0000 \u0000 This paper makes a contribution to the advancement of artificial intelligence in the context of multi-agent planning for large-scale combat scenarios in RTS games. This paper introduces Fast Random Genetic Search (FRGS), a genetic algorithm which is characterized by a small active population, a crossover technique which produces only one child, dynamic mutation rates, elitism, and restrictions on revisiting solutions. This paper demonstrates the effectiveness of FRGS against a static AI and a dynamic AI using the Portfolio Greedy Search (PGS) algorithm. In the context of the popular Real-Time Strategy (RTS) game, StarCraft, this paper shows the advantages of FRGS in combat scenarios up to the maximum size of 200 vs. 200 units under a 40 ms time constraint.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"38 1","pages":"165-171"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81699956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Predicting Proppian Narrative Functions from Stories in Natural Language 从自然语言中预测故事的叙事功能
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v12i1.12855
Josep Valls-Vargas, Jichen Zhu, Santiago Ontañón
{"title":"Predicting Proppian Narrative Functions from Stories in Natural Language","authors":"Josep Valls-Vargas, Jichen Zhu, Santiago Ontañón","doi":"10.1609/aiide.v12i1.12855","DOIUrl":"https://doi.org/10.1609/aiide.v12i1.12855","url":null,"abstract":"\u0000 \u0000 Computational narrative systems usually require knowledge about the story world and narrative theory to be encoded in some form of structured knowledge representation formalism, a notoriously time-consuming task requiring expertise in both storytelling and knowledge engineering. In this paper we present an approach that combines supervised machine learning with narrative domain knowledge toward automatically extracting such knowledge from natural language stories, focusing specifically on predicting Proppian narrative functions. Our experiments on a dataset of Russian fairy tales show that our system outperforms an informed baseline and that combining top-down narrative theory and bottom-up statistical models inferred from an annotated dataset increases prediction accuracy with respect to using them in isolation.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"59 1","pages":"107-113"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83195805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
LISA: Lexically Intelligent Story Assistant 丽莎:词汇智能故事助手
Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-06-25 DOI: 10.1609/aiide.v13i1.12956
Rushit Sanghrajka, Daniel Hidalgo, Patrick P. Chen, Mubbasir Kapadia
{"title":"LISA: Lexically Intelligent Story Assistant","authors":"Rushit Sanghrajka, Daniel Hidalgo, Patrick P. Chen, Mubbasir Kapadia","doi":"10.1609/aiide.v13i1.12956","DOIUrl":"https://doi.org/10.1609/aiide.v13i1.12956","url":null,"abstract":"\u0000 \u0000 This paper serves as an introduction to building an assistive tool for story writers. Our tool, Lexically Intelligent Story Assistant (or LISA), aims to assist story writers by providing real-time feedback on lexical inconsistencies in the story. LISA analyzes the narrative and builds a knowledge base, using artificial intelligence to make inferences and point out errors in the narrative. Moreover, it also allows the user to interact with the system by querying the knowledge base in natural language form. This tool shows that it is possible to create a database for a narrative and use artificial intelligence to improve authoring of stories.\u0000 \u0000","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"11 1","pages":"221-227"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81328009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
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